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PWM逆变器全图，共有四组不同参数仿真,包你下载不后悔(PWM inverter full size, a total of four simulations with different parameters, including your download does not regret)

线性调频信号仿真，及时域频域脉冲压缩，加窗处理抑制旁瓣(LFM signal simulation, pulse compression in time domain and frequency domain, windowed processing to suppress sidelobes)

说明：  根据轴承实验数据，处理轴承内外圈的实验数据，根据频谱进行数据分析。(According to the bearing experimental data, the experimental data of bearing inner and outer rings are processed, and the data are analyzed according to the spectrum.)

优秀论文及配套源码。电压暂降是动态电能质量问题中最受关注的热点之一。大量新型电力电子设备的广泛使用对电网电能质量的要求越来越高，而且电压暂降在电网中又具有一定的传播性。因此，无论从电网还是用户都迫切需要对电压暂降进行研究和治理。对电压暂降的检测是解决电压暂降的前提条件，故本论文主要对电压暂降的检测方法进行研究。 本文分析了国内外短时电能质量扰动检测的研究现状，并着重讨论了短路故障、感应电动机启动和变压器激磁三种电压暂降扰动情况下电压暂降的特性；在此基础上选择了基于S变换的短时电能质量扰动检测方法，从S变换的结果S模矩阵及S复矩阵中提取出所需数据并以此来对各种扰动情况下的电压暂降的幅值、相位跳变、持续时间和谐波含量进行分析。仿真结果表明，该方法很好地实现了对电压暂降各特征量的检测。 (The voltage sag is one of most hot topics in dynamic electric energy problems. Masses of new power and electron facilities have been put into use widely, requiring a high quality of electric network and power, chiefly the voltage sag. Moreover, the voltage sag can spread in the electric network. So people have every reason to research and control the voltage sag. However, before developing the voltage sag, people have to detect it. On account of the above, this essay will chiefly focus on the detect methods of the voltage sags. In this paper, the status of the short duration power quality disturbance based on the different method are researched firstly, and emphasizes the characteristic of the voltage sag under the situation of the three kinds of voltage sag disturbances like the short circuit fault, induction motor start-up and transformer excitation. On the basis of the above, the short duration power quality disturbance detection method based on S transform is chosen. The complex m)

前项平滑技术，是空间普技术中解相干的一种重要方法(former smoothing technology, space technology Pronk decorrelation an important method)

For quantum well Schrodinger poisson

实现六自由度并联机器人的运动控制 simulink仿真(Implementation of 6 dof parallel robot movement control simulink simulation)

基于极限学习机和BP神经网络的半监督分类算法(Semi supervised classification algorithm based on extreme learning machine and BP neural network)

该演示中包含的代码演示如何氡相似的功能，可以用来提高（以及部分）在Connectome电磁图像单元格边界。 请举出下列文件如果您发现此代码有用： Ritwik库马尔，阿梅里奥五雷纳和Hanspeter Pfister说“氡样的特点及其应用Connectomics”，接受，IEEE计算机学会研讨会在生物医学图像分析（MMBIA）2010年数学方法 http://seas.harvard.edu/〜 rkkumar radonLikeFeaturesDemo.m：演示边缘增强用氡相似的功能， getEdgeFeatures.m：助手为高斯函数的二阶导数滤波器 makeBarFilters.m：助手为高斯函数的二阶导数滤波器 sample.png：示例图像在此演示使用(The demo included in the code demonstrates how Radon-Like Features can be used to enhance (and segment) cell boundaries in Connectome EM images. Please cite the following paper if you find this code useful: Ritwik Kumar, Amelio V. Reina & Hanspeter Pfister, “Radon-Like Features and their Application to Connectomics”, accepted, IEEE Computer Society Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA) 2010 http://seas.harvard.edu/~rkkumar radonLikeFeaturesDemo.m : Demonstrates edge enhancement using Radon-Like Features getEdgeFeatures.m : Helper function for Gaussian Second Derivative Filters makeBarFilters.m : Helper function for Gaussian Second Derivative Filters sample.png : Sample image for use in this demo )

说明：  飞行模拟转台伺服系统仿真 S为信号变量 1为正弦 2为阶跃 3为方波(flight simulation turntable servo system simulation S signal to a variable sinusoidal Step 2 for 3 for the square wave)